The present disclosure relates to image processing for detecting selected objects in an image, and more particularly to the utilization of context-driven label propagation to identify groups of selected objects in crowded and/or cluttered scenes.
The need to detect and/or identify selected objects such as people or vehicles in images is central to a wide range of applications such as video surveillance and autonomous driving. Object detection for individuals and vehicles has been utilized in a variety of systems, including, for example, computer vision, deformable part models (DPM), poselets and deep learning. Object detection is particularly challenging when the objects in a given scene are at least partially obstructed or unclear because of a cluttered background, or because of the large number of potential pose variations.